Applying Intuitionistic Fuzzy Sets to Improve Fuzzy Content-based Image Retrieval Systems

Azimi Hemat, Monireh; Valipour, Ezat; Ali Ahmadipoor, Laya

doi:10.22044/jadm.2025.14597.2568

Document Type : Original/Review Paper

Authors

¹ Department of Computer science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran.

² Department of Applied Mathematics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran.

https://doi.org/10.22044/jadm.2025.14597.2568

Abstract

Visual features extracted from images in content-based image retrieval systems are inherently ambiguous. Consequently, applying fuzzy sets for image indexing in image retrieval systems has improved eﬃciency. In this article, the intuitionistic fuzzy sets are used to enhance the performance of the Fuzzy Content-Based Image Retrieval (F-CBIR) system. To this aim, an Intuitionistic Fuzzy Content-Based Image Retrieval (IF-CBIR) is proposed by applying intuitionistic fuzzy generators on fuzzy sets. Due to the diversity of the intuitionistic fuzzy distance measure, several are assessed in IF-CBIR; in these assessments, the measure with higher performance is identiﬁed. Finally, the proposed IF-CBIR and the existing crisp CBIR and F-CBIR simulate on Corel 5K and Corel 10K databases. The results show that our proposed method has higher (10-15%) precision compared to the mentioned methods.

Keywords

Main Subjects

H.3. Artificial Intelligence

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Applying Intuitionistic Fuzzy Sets to Improve Fuzzy Content-based Image Retrieval Systems

References

References

Volume 13, Issue 1January 2025Pages 63-73

Volume 13, Issue 1
January 2025
Pages 63-73